Protein folding and dynamics are integral to many biological activities, including chaperone action, protein degradation, amyloid diseases and aging. Our goal is to combine experimental and computational studies to produce a predictive understanding of folding behavior for proteins, independent of whether they are naturally occurring, designed, unfolded, or intrinsically disordered. Our ? analysis method identifies transition states as large and native-like and, along with other data, argues that folding occurs via a process of sequential stabilization. Aim 1 describes our planned tests of whether this mechanism applies to the whole pathway, especially the early portions. In parallel, we will advance our unifying framework for predicting both pathways and structure using only the sequence as input. Although the method is based only on basic principles of protein chemistry, it has an accuracy comparable to the best MD simulations. We will provide high-resolution data for different proteins to test our simulations and those of others, including DESRES, a collaborator. Aim 2 delineates how we will investigate whether the unfolded state compacts under native conditions. FRET and MD simulations indicate yes, whereas small angle X-ray scattering indicates otherwise. We will probe the origins of this perplexing discrepancy that has implications to folding mechanisms, the validity of MD simulations, and biothermodynamics. Aim 3 summarizes our proposed comparison of the folding of naturally occurring proteins and novel designed folds with complex folding kinetics. Identifying the origin of the complex kinetics both challenges our understanding and can help improve design algorithms.